Translational Control of Cell Fate: Availability of Phosphorylation Sites on Translational Repressor 4E-BP1 Governs Its Proapoptotic Potency
Bibliographic record
Abstract
Translational control has been recently added to well-recognized genomic, transcriptional, and posttranslational mechanisms regulating apoptosis. We previously found that overexpressed eukaryotic initiation factor 4E (eIF4E) rescues cells from apoptosis, while ectopic expression of wild-type eIF4E-binding protein 1 (4E-BP1), the most abundant member of the 4E-BP family of eIF4E repressor proteins, activates apoptosis--but only in transformed cells. To test the possibility that nontransformed cells require less cap-dependent translation to suppress apoptosis than do their transformed counterparts, we intensified the level of translational repression in nontransformed fibroblasts. Here, we show that inhibition of 4E-BP1 phosphorylation by rapamycin triggers apoptosis in cells ectopically expressing wild-type 4E-BP1 and that expression of 4E-BP1 phosphorylation site mutants potently activates apoptosis in a phosphorylation site-specific manner. In general, proapoptotic potency paralleled repression of cap-dependent translation. However, this relationship was not a simple monotone. As repression of cap-dependent translation intensified, apoptosis increased to a maximum value. Further repression resulted in less apoptosis--a state associated with activation of translation through internal ribosomal entry sites. These findings show: that phosphorylation events govern the proapoptotic potency of 4E-BP1, that 4E-BP1 is proapoptotic in normal as well as transformed fibroblasts, and that malignant transformation is associated with a higher requirement for cap-dependent translation to inhibit apoptosis. Our results suggest that 4E-BP1-mediated control of apoptosis occurs through qualitative rather than quantitative changes in protein synthesis, mediated by a dynamic interplay between cap-dependent and cap-independent processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".